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Intelligent control for a drone by self-tunable Fuzzy Inference System

descriptionPublicationkeyboard_double_arrow_right Conference object , Article 01 Mar 2009 France Publisher:IEEEJournal:2009 6th International Multi-Conference on Systems, Signals and Devices
Authors: Zemalache, Kadda; Maaref, Hichem;

doi: 10.1109/ssd.2009.4956805

Intelligent control for a drone by self-tunable Fuzzy Inference System

Abstract

The work describes an automatically on-line Self-Tunable Fuzzy Inference System (STFIS) of a new configuration of mini-flying called XSF (X4 Stationnary Flyer) drone. A Fuzzy controller based on on-line optimization of a zero order Takagi-Sugeno fuzzy inference system (FIS) by a back propagation-like algorithm is successfully applied. It is used to minimize a cost function that is made up of a quadratic error term and a weight decay term that prevents an excessive growth of parameters. Thus, we carried out control for the continuation of simple trajectories such as the follow-up of straight lines, and complex (half circle, corner) by using the STFIS technique. This permits to prove the effectiveness of the proposed control law. We studied the robustness of the two controllers used in the presence of disturbances. We presented two types of disturbances, the case of a gust of wind and taking into account white noise disturbances. A comparison between the Self-Tunable Fuzzy Inference System (STFIS) and Adaptive Network based Fuzzy Inference System (ANFIS) is given.

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Keywords

[SPI.SIGNAL] Engineering Sciences/Signal and Image processing, [ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing, Tracking control, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Static feedback linearization controller, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Self-tunable fuzzy inference system, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [ SPI.AUTO ] Engineering Sciences [physics]/Automatic, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, AUTO] Engineering Sciences/Automatic [[SPI], SIGNAL] Engineering Sciences/Signal and Image processing [[SPI], SIGNAL] Sciences de l'ingénieur/Traitement du signal et de l'image [[SPI], [INFO.INFO-TS] Computer Science/Signal and Image Processing, Drone, AUTO] Sciences de l'ingénieur/Automatique / Robotique [[SPI], [SPI.AUTO] Engineering Sciences/Automatic, [SPI.AUTO] Engineering Sciences [physics]/Automatic, INFO_TS] Informatique/Traitement du signal et de l'image [[INFO], INFO_TS] Computer Science/Signal and Image Processing [[INFO], [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Top 10%
Average
Green